A 2026 Gartner survey of 1,865 employees found that only 21 percent of time freed up by artificial intelligence was redirected into more innovative work.
“There isn’t a struggle to create capacity; that’s happening already as organizations redesign work,” said C.V. Viverito, Gartner senior director. “What organizations are struggling with is how to make that capacity usable and redirecting it to what is valuable.”
We really should not be surprised. How many entities have a really good grasp on what activities and functions produce the most value, compared to others? And how long has it taken for prior general-purpose technologies to be incorporated into changed work flows and business processes? Much longer than just a few years, as it turns out.
That might be old news to an economic historian, but provide scant comfort for an active investor.
In fact, general-purpose technologies have typically required 15 to 40 years from commercial introduction or widespread availability until work processes and organizations were substantially redesigned, producing clear economy-wide productivity gains.
That is an incomprehensible time frame for today’s investors, focused on quarterly and yearly observable results. So disillusionment will be inevitable, despite strenuous efforts by participants to show outcomes in the near term.
The pattern is that early adoption often involved bolting the new technology onto old processes, producing limited benefits. The full benefits arrived only after complementary investments in firm organization, skills, infrastructure and workflows.
This is the core of the “productivity paradox” or “J-curve” for GPTs: measured productivity can lag or even dip initially while firms invest in hard-to-measure intangibles (process redesign, training, data systems, management changes).
Some might characterize the current “anti-AI” sentiment as a moral panic. A moral panic is a widespread, exaggerated feeling of fear that a specific group, behavior, or cultural shift poses a severe and immediate threat to the values, safety, or well-being of society.
Such technology panics often last from five to 15 years for the intense phase. So we might have to deal with this for a while. In other cases, they run their course in five years or less.
Past panics have included fears about (job displacement, cultural degradation, loss of agency, existential risk, corruption of youth/creativity:
Comic books (late 1940s–mid-1950s): Concern built through the late 1940s with burnings and local campaigns. Peak intensity came with Fredric Wertham’s Seduction of the Innocent (1954) and U.S. Senate hearings that same year. The industry imposed the Comics Code Authority almost immediately. Intense public/political pressure largely faded by the late 1950s; sales and cultural centrality of the medium never fully recovered in the same form, but the acute panic phase was roughly a decade or less from ramp-up to cooling.
Video games and violent games: Early arcade and “Death Race”-style concerns in the late 1970s–early 1980s. Stronger national intensity in the early–mid 1990s (Mortal Kombat hearings, Lieberman, ESRB creation). Columbine (1999) produced another spike into the 2000s. The most feverish “games cause mass violence” phase lasted roughly a decade-plus of high visibility before declining as evidence failed to support the strongest claims and the medium normalized. Residual skepticism persists in some circles, but it is no longer a dominant media/political frenzy.
Satanic Panic / ritual abuse (roughly 1980–early/mid-1990s): Sparked by books like Michelle Remembers, day-care cases (McMartin starting 1983), heavy metal, and D&D. Peak media and legal intensity in the mid-to-late 1980s; major trials and coverage continued into the early 1990s. By the mid-1990s skepticism, failed prosecutions, and shifting attention largely ended the broad panic (though echoes remain in niche conspiracy thinking). Core duration: about a decade to 15 years.
Other shorter or cyclical cases: “Stranger danger,” specific drug scares, or one-off media challenges often rise and fall in one to five years. Persistent or recurring ones (certain drug wars, immigration waves) can last decades or cycle, but pure technology/entertainment panics more often follow the shorter pattern once the technology becomes ubiquitous and a generation grows up with it.
If the current wave of opposition to AI (existential risk narratives, mass unemployment fears, “slop” cultural degradation, student cheating, etc.) fits the moral-panic pattern, history suggests the most intense, media-saturated, policy-driving phase would typically run on the order of several years to roughly a decade or a bit more from peak visibility.
Generative AI tools became widely public around late 2022; by late 2026 we are a few years in. Normalization tends to occur as people use the technology daily, evidence of actual harms is tested against claims, younger cohorts treat it as ordinary infrastructure, and attention moves to the next novelty or crisis.
Either way, AI value chain participants are going to have to deal with policymakers and regulatory concerns for some time, ranging from several years to a decade, possibly. At the same time, they will be doing their very best to highlight near-term benefits to the extent they can, even if history suggests the real benefits will be a ways off.
